Product Management Is Dead. Long Live Product Management.

Howie Liu, co-founder and CEO of Airtable for 13 years, faced an existential moment when a viral tweet declared "Airtable is dead." His response was not to tweak the PM role but to collapse the walls between PM, design, and engineering entirely.

"It really does become more about individual attitude. There's a strong advantage to any of those three roles who can kind of cross over into the other two. As a PM, you need to start looking more like a hybrid PM prototyper, who has some good design sensibilities."

Howie Liu

▶ 00:00:33

Liu restructured Airtable's EPD org into two groups: a "fast thinking" group focused on rapid AI experimentation with startup-like urgency, and a "slow thinking" group maintaining the core platform. Half of EPD now works on AI capabilities. He runs weekly sprint check-ins and benchmarks against the pace of AI-native startups:

"I basically want to always ask the question, how would an AI native company, like a Cursor or Windsurf, how would they execute? And are we executing as fast as them and taking advantage of all the new stuff as well as them?"

Howie Liu

▶ 00:18:29

Liu himself embodies the change he demands. He has become what Lenny calls an "IC CEO" -- getting back into the code, building personally, leading initiatives directly. He encourages his team to cancel all meetings for a day or a week to experiment with AI products. And his litmus test for any established company is brutal:

"If you were literally founding a new company from scratch with the same mission, how would you execute on that mission using a fully AI native approach? If you can't, then you should find a buyer."

Howie Liu

▶ 00:00:00

Chip Huyen, a core developer on NVIDIA's NeMo platform, Stanford ML instructor, and author of the most-read book on the O'Reilly platform, brings the most empirically grounded perspective. She works with enterprises on AI strategy and sees contradictory data on the ground.

Her most striking finding: a company divided engineers into three performance tiers and gave half of each group access to Cursor. The highest-performing engineers gained the most. The lowest performers actually got worse -- they went on autopilot with AI-generated code or did not know enough to use the tools effectively. But another company reported the exact opposite: their senior engineers were the most resistant, finding AI code quality below their standards.

"The biggest performance boost was the senior engineer, the highest performing. So the highest performing engineers is also normal practice. They also know how to solve problems."

Chip Huyen

▶ 00:46:41

"Another company, however, they tell me just actually, senior engineers are the one most resistant to using AI as this tooling because they are more opinionated and they have very high standard."

Chip Huyen

▶ 00:47:30

Huyen's most contrarian point cuts against the hype: she argues we are in an "ideal crisis" -- incredible tools but people stuck because they do not know what to build. Her viral comparison of what people think improves AI apps (chasing AI news, adopting frameworks) vs. what actually does (talking to users, preparing better data) suggests the PM fundamentals have not changed as much as the tooling.

Even productivity perception is structurally shaped by who you ask: managers prefer headcount, executives prefer AI tools. The measurement problem itself may be unsolvable in the traditional way.

Dan Shipper, co-founder and CEO of Every, operates a 15-person company that runs a daily newsletter (100K subscribers, read by top AI lab researchers), four software products, and a consulting arm -- all with zero handwritten code. He believes what his team does today, everyone else will do in three years.

"No one is manually coding anymore. Organizations like ours, people who are playing at the edge, we're doing things that, in three years, everybody else is going to be doing."

Dan Shipper

▶ 00:00:46

The key organizational enabler is a dedicated "head of AI operations." Shipper meets with her weekly; every time he identifies a repetitive task, it goes on a list. She builds prompts and workflows so the entire team offloads repetitive work. This role exists because most people, under daily work pressure, default to familiar methods rather than experimenting with AI.

Through his consulting work with large companies -- including a $10 billion hedge fund -- Shipper has identified the single strongest predictor of successful AI adoption:

"The number one predictor is, 'Does the CEO use ChatGPT?' If the CEO is in it all the time, being like, 'This is the coolest thing,' everybody else is going to start doing it. If the CEO is like, 'I don't know, this is for someone else,' no one else is going to be able to lead that charge."

Dan Shipper

▶ 01:12:00

Shipper is forcefully optimistic about junior workers. One junior employee made a year's worth of progress in two months by recording every piece of feedback, converting it into prompts, and never making the same mistake twice. AI does not replace juniors -- it compounds their learning.

Eoghan McCabe, founder of Intercom (14+ years), returned as CEO during a crisis. The company had experienced five consecutive quarters of declining net new ARR and was approaching negative growth. One month after his return, ChatGPT launched. What followed is perhaps the most aggressive AI transformation of any established SaaS company.

"I said, we need to become a wartime company. If we don't fight for this, we are dead. I jumped hard on AI, but I also restarted the culture. I rewrote the values designed to be a sharp knife to cut out the parts of the company that I just knew wouldn't be effective."

Eoghan McCabe

▶ 00:00:33

McCabe made three simultaneous moves. He rewrote Intercom's values as a deliberate filter. He drove 40% employee turnover through culture changes that made the old way of working untenable. And he went all-in on Fin, their AI agent. The speed was extraordinary: just six weeks after GPT-3.5 launched, they had a working beta.

"We were only six weeks into the launch of GPT 3.5 when we actually had a beta version of Fin. I got a text from Des, my co-founder, a week or so after the launch of GPT 3.5 and he said, 'The AI team have something interesting and they actually think we could make a product out of this.'"

Eoghan McCabe

▶ 00:10:52

The results: Fin now grows at 300%+, on track to pass $100M ARR in under three quarters. Intercom ranks in the 15th percentile for ARR growth among 120+ public B2B software companies. McCabe is honest about survivorship bias -- "we were coming from a point of having nothing to lose" -- but insists the principle generalizes: "The way that greatness is created is that you find a CEO who's willing to make brave hard decisions and own the results."

Advocates: Nikhyl Singhal, Founder; former product executive at Meta, Google, and Credit Karma, Skip

Agents make organizational ground truth easier to retrieve and can automate the mechanical production and coordination work that consumed traditional PM time. At the same time, cheap implementation creates ten to one hundred times more possible changes, so scarcity moves to deciding which changes improve the product as a coherent system, preserve differentiation and maintainability, and deserve release.

Companies will therefore shed coordination-heavy roles while rehiring fewer AI-first builders and paying product leaders for judgment rather than information relay.

"I think on the company side, I think that, and then maybe I'll slant it more towards product for a second. Product leaders will increasingly get paid and be asked to drive judgment, and then be the tip of the sphere on trying to essentially obsolete everything else through software, through AI, through agents. This is partly why there's a lot of excitement, because just to be very honest with you and you were a PM and I was a PM, most of the stuff that you didn't like doing are the things that AI is really taking a real crack at. I think that's super interesting. I think that there's a ton of that change that's going to happen. Some companies are doing it now, some companies will do it, but within two years I think most of these companies will obsolete all the mechanical parts of building product."

Nikhyl Singhal

▶ 00:14:34

"I think that it's evaluating whether the thing that we're changing is a good or bad thing. I think that it's also evaluating whether we should change the product in one way versus another. You can't build a hundred custom versions of the same product. It affects your brand, it affects the maintainability, et cetera. When customers are asking for things, when you're trying to think through how do you build something that's sustainable, differentiated, that's judgment. Evaluating whether it's successfully met that criteria and whether it's worth building and worth releasing, it's almost like the system skill that's existed from the beginning of the internet. It's, "Hey, it's not about the feature, it's around the system that we're putting together, the platform, if you will, that's enabling capability.""

Nikhyl Singhal

▶ 00:15:57